70 Result(s)
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Article
**-Peng Li
Computer Science
Artificial Intelligence
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Article
A Novel Memristors Based Echo State Network Model Inspired by the Brain’s Uni-hemispheric Slow-Wave Sleep Characteristics
Memristors serve as electronic components with the ability to store charge and demonstrate resistive states, which are similar to the synaptic connections between biological neurons. For this reason, they have...
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Dynamic context-driven progressive image inpainting with auxiliary generative units
Image inpainting aims to restore missing or damaged regions of an image with plausible visual content. Most existing methods always face challenges when dealing with large hole images, such as structural disto...
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Facial expression recognition based on local–global information reasoning and spatial distribution of landmark features
In the field of facial expression recognition (FER), two main trends point to the data-driven FER and feature-driven FER exist. The former focused on the data problems (e.g., sample imbalance and multimodal fu...
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SAIH: A Scalable Evaluation Methodology for Understanding AI Performance Trend on HPC Systems
Novel artificial intelligence (AI) technology has expedited various scientific research, e.g., cosmology, physics, and bioinformatics, inevitably becoming a significant category of workload on high-performance...
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Enhancing Storage Efficiency and Performance: A Survey of Data Partitioning Techniques
Data partitioning techniques are pivotal for optimal data placement across storage devices, thereby enhancing resource utilization and overall system throughput. However, the design of effective partition sche...
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SRENet: Structure recovery ensemble network for single image deraining
Single-image deraining remains a formidable challenge. Its objective is not only to eliminate rain streaks from the target image but also to restore its spatial details and high-level contextual structure. Rec...
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CLIP-Adapter: Better Vision-Language Models with Feature Adapters
Large-scale contrastive vision-language pretraining has shown significant progress in visual representation learning. Unlike traditional visual systems trained by a fixed set of discrete labels, a new paradigm...
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Research on General-Purpose Brain-Inspired Computing Systems
Brain-inspired computing is a new technology that draws on the principles of brain science and is oriented to the efficient development of artificial general intelligence (AGI), and a brain-inspired computing ...
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V \(^2\) MLP: an accurate and simple multi-view MLP network for fine-grained 3D shape recognition
Fine-grained 3D shape recognition (FGSR) is crucial for real-world applications. Existing methods face challenges in achieving high accuracy for FGSR due to high similarity within sub-categories and low dissim...
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Adversarial-Based Ensemble Feature Knowledge Distillation
Existing knowledge distillation methods usually consider class probabilities or directly align features, which ignore the rich information contained in high-level feature maps. In this paper, we propose a nove...
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MapReduce-based distributed tensor clustering algorithm
Cluster analysis is one of the most fundamental methods in data mining, and it has been widely used in economics, social sciences and computer science. However, with the rapid development of Internet technolog...
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Principal relation component reasoning-enhanced social relation recognition
Social relationships (SRs) are the basis of human life. Hence, the ability to accurately recognize interpersonal relations in public spaces based on visual observations helps policymakers improve mental health...
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Aspect-Based Sentiment Analysis Using Adversarial BERT with Capsule Networks
Aspect-based sentiment analysis aims to predict the sentiment polarity of a given aspect in a sentence. The previous methods based on RNNs and attention mechanisms mainly have two problems: (1) The datasets fo...
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Open AccessA systematic review of deep learning-based cervical cytology screening: from cell identification to whole slide image analysis
Cervical cancer is one of the most common cancers in daily life. Early detection and diagnosis can effectively help facilitate subsequent clinical treatment and management. With the growing advancement of arti...
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Classifying ambiguous identities in hidden-role Stochastic games with multi-agent reinforcement learning
Multi-agent reinforcement learning (MARL) is a prevalent learning paradigm for solving stochastic games. In most MARL studies, agents in a game are defined as teammates or enemies beforehand, and the relations...
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Evaluating RISC-V Vector Instruction Set Architecture Extension with Computer Vision Workloads
Computer vision (CV) algorithms have been extensively used for a myriad of applications nowadays. As the multimedia data are generally well-formatted and regular, it is beneficial to leverage the massive paral...
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Improving BERT Fine-Tuning via Self-Ensemble and Self-Distillation
Fine-tuning pre-trained language models like BERT have become an effective way in natural language processing (NLP) and yield state-of-the-art results on many downstream tasks. Recent studies on adapting BERT ...
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PESTA: An Elastic Motion Capture Data Retrieval Method
Prevalent use of motion capture (MoCap) produces large volumes of data and MoCap data retrieval becomes crucial for efficient data reuse. MoCap clips may not be neatly segmented and labeled, increasing the dif...
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PCRTAM-Net: A Novel Pre-Activated Convolution Residual and Triple Attention Mechanism Network for Retinal Vessel Segmentation
Retinal images play an essential role in the early diagnosis of ophthalmic diseases. Automatic segmentation of retinal vessels in color fundus images is challenging due to the morphological differences between...
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Open AccessJNeRF: An efficient heterogeneous NeRF model zoo based on Jittor
